nubia NX669J
Geekbench ML Score
700
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 08:48 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | nubia NX669J |
| Model ID | nubia NX669J |
| Motherboard | lahaina |
| Governor | performance |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
301
56.3 IPS |
|
|
Image Classification (F16)
|
100% |
289
54.1 IPS |
|
|
Image Classification (I8)
|
97% |
727
136.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
396
6.61 IPS |
|
|
Image Segmentation (F16)
|
100% |
397
6.63 IPS |
|
|
Image Segmentation (I8)
|
98% |
549
9.17 IPS |
|
|
Pose Estimation (F32)
|
100% |
717
0.87 IPS |
|
|
Pose Estimation (F16)
|
100% |
712
0.86 IPS |
|
|
Pose Estimation (I8)
|
100% |
3538
4.28 IPS |
|
|
Object Detection (F32)
|
100% |
328
24.5 IPS |
|
|
Object Detection (F16)
|
100% |
318
23.7 IPS |
|
|
Object Detection (I8)
|
61% |
902
67.3 IPS |
|
|
Face Detection (F32)
|
100% |
681
8.10 IPS |
|
|
Face Detection (F16)
|
100% |
668
7.94 IPS |
|
|
Face Detection (I8)
|
86% |
1819
21.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
765
5.94 IPS |
|
|
Depth Estimation (F16)
|
100% |
771
5.98 IPS |
|
|
Depth Estimation (I8)
|
95% |
1973
15.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1443
1.90 IPS |
|
|
Style Transfer (F16)
|
100% |
1449
1.91 IPS |
|
|
Style Transfer (I8)
|
98% |
3203
4.21 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
468
16.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
477
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1412
50.4 IPS |
|
|
Text Classification (F32)
|
100% |
388
557.6 IPS |
|
|
Text Classification (F16)
|
100% |
376
540.7 IPS |
|
|
Text Classification (I8)
|
92% |
362
520.3 IPS |
|
|
Machine Translation (F32)
|
100% |
786
14.5 IPS |
|
|
Machine Translation (F16)
|
100% |
807
14.9 IPS |
|
|
Machine Translation (I8)
|
64% |
363
6.68 IPS |
